Search results for: bilingual content subject learning

Authors: Sanghoon Shim, Jaehwan Jung, Sung-Ah Kim

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As the digital technology develops, studies on the TUI (Tangible User Interface) that links the physical environment utilizing the human senses with the virtual environment through the computer are actively being conducted. In addition, there has been a tremendous advance in computer design making through the use of computer-aided design techniques, which enable optimized decision-making through comparison with machine learning and parallel comparison of alternatives. However, a complex design that can respond to user requirements or performance can emerge through the intuition of the designer, but it is difficult to actualize the emerged design by the designer's ability alone. Ancillary tools such as Gaudí's Sandbag can be an instrument to reinforce and evolve emerged ideas from designers. With the advent of many commercial tools that support 3D objects, designers' intentions are easily reflected in their designs, but the degree of their reflection reflects their intentions according to the proficiency of design tools. This study embodies the environment in which the form can be implemented by the fingers of the most basic designer in the initial design phase of the complex type building design. Leapmotion is used as a sensor to recognize the hand motions of the designer, and it is converted into digital information to realize an environment that can be linked in real time in virtual reality (VR). In addition, the implemented design can be linked with Rhino™, a 3D authoring tool, and its plug-in Grasshopper™ in real time. As a result, it is possible to design sensibly using TUI, and it can serve as a tool for assisting designer intuition.

Keywords: design environment, digital modeling, hand gesture, TUI, virtual reality

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Authors: Popoola Sulaimon Akorede, Muinat A. Agbabiaka-Mustapha

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The Quranic / piazza school where the rudiments of Islam are being imparted from the teaching of Arabic/ Quranic alphabets which later metamorphosized to higher fundamental principles of Islam is the major determinant of the existence of Islam in any part of south western Nigeria. In other words, one can successfully say that where there is a few or non-existence of such schools in that part of the country, the practice of the religion of Islam would be either very low or not existing at all. However, it has been discovered in the modern worlds that several challenges are militating against the development of these schools and among these challenges are poor admission policy, inadequate facilities such as learning environment and instructional materials, curriculum inadequacy and the management and the administration of the schools which failed to change in order to meet the modern contemporary Educational challenges. The focus of this paper therefore is to improve the conditions of these basic Islamic schools through the introduction of quality assurance and integrating accreditation Exercise to improve their status in order to enhance economic empowerment and to further their educational career in the future so that they will be able to compete favourably among the graduates of conventional universities. The scope of this study is limited to only seven (7) states of yorubaland and with only three (3) proprietors/ schools from each state which are Lagos, Oyo, Ogun, Osun, Ekiti, Ondo and parts of Kwara State. The study revealed that quality assurance as well as accreditation exercise are lacking in all the local Arabic/Quranic schools. Suggestions are proffered towards correcting the anomalies in these schools so that they can meet the modern Educational standard.

Keywords: accreditation, quality assurance, Quranic schools, South-western Nigeria

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Authors: Daniel Ihemtuge Akim, Micheal O. Ikeanumba

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This research focused on team teaching; students perception, challenges, and remedies for effective implementation, a case study of the department of Biology, Alvan Ikoku Federal College of Education, Owerri Imo State, Nigeria. It seeks to address the misconception by students on the use of team teaching as a methodology for learning. Five purposes and five research questions guided this study. Descriptive survey design was used in the study. The students of biology department enrolled in both Bachelor degree and National Certificate in Education in Alvan Ikoku Federal College of Education, Owerri, formed the population size. Simple random sampling technique was used to select the sampled students and 20% of whole lecturers were selected out of the whole given sample size of three hundred and forty (340). The instrument used for data collection was structured 4 point Likert scale questionnaire and analysis was made using mean method. The result revealed that poor time management by lectures, lack of lecture venues, manpower are some of the challenges hindering the effective implementation of team teaching. It was also observed that students perform better in academic when team teaching approach is used than single teaching approach. Finally, recommendations made suggested that teachers involved in team teaching should work together with their teaching strategies and within the time frame to achieve the stated objectives.

Keywords: challenges, implementation, perception, team teaching

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Authors: Valeria Aman

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The presented study examines the impact of international mobility on knowledge production among mobile scientists and within the sending and receiving research groups. Scientists are relevant to the dynamics of knowledge production because scientific knowledge is mainly characterized by embeddedness and tacitness. International mobility enables the dissemination of scientific knowledge to other places and encourages new combinations of knowledge. It can also increase the interdisciplinarity of research by forming synergetic combinations of knowledge. Particularly innovative ideas can have their roots in related research domains and are sometimes transferred only through the physical mobility of scientists. Diversity among scientists with respect to their knowledge base can act as an engine for the creation of knowledge. It is therefore relevant to study how knowledge acquired through international mobility affects the knowledge production process. In certain research domains, international mobility may be essential to contextualize knowledge and to gain access to knowledge located at distant places. The knowledge production process contingent on the type of international mobility and the epistemic culture of a research field is examined. The production of scientific knowledge is a multi-faceted process, the output of which is mainly published in scholarly journals. Therefore, the study builds upon publication and citation data covered in Elsevier’s Scopus database for the period of 1996 to 2015. To analyse these data, bibliometric and social network analysis techniques are used. A basic analysis of scientific output using publication data, citation data and data on co-authored publications is combined with a content map analysis. Abstracts of publications indicate whether a research stay abroad makes an original contribution methodologically, theoretically or empirically. Moreover, co-citations are analysed to map linkages among scientists and emerging research domains. Finally, acknowledgements are studied that can function as channels of formal and informal communication between the actors involved in the process of knowledge production. The results provide better understanding of how the international mobility of scientists contributes to the production of knowledge, by contrasting the knowledge production dynamics of internationally mobile scientists with those being nationally mobile or immobile. Findings also allow indicating whether international mobility accelerates the production of knowledge and the emergence of new research fields.

Keywords: bibliometrics, diversity, interdisciplinarity, international mobility, knowledge production

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Authors: Ritwik Dutta, Marylin Wolf

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This paper describes the trade-offs and the design from scratch of a self-contained, easy-to-use health dashboard software system that provides customizable data tracking for patients in smart homes. The system is made up of different software modules and comprises a front-end and a back-end component. Built with HTML, CSS, and JavaScript, the front-end allows adding users, logging into the system, selecting metrics, and specifying health goals. The back-end consists of a NoSQL Mongo database, a Python script, and a SimpleHTTPServer written in Python. The database stores user profiles and health data in JSON format. The Python script makes use of the PyMongo driver library to query the database and displays formatted data as a daily snapshot of user health metrics against target goals. Any number of standard and custom metrics can be added to the system, and corresponding health data can be fed automatically, via sensor APIs or manually, as text or picture data files. A real-time METAR request API permits correlating weather data with patient health, and an advanced query system is implemented to allow trend analysis of selected health metrics over custom time intervals. Available on the GitHub repository system, the project is free to use for academic purposes of learning and experimenting, or practical purposes by building on it.

Keywords: flask, Java, JavaScript, health monitoring, long-term care, Mongo, Python, smart home, software engineering, webserver

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Authors: Lee Artz

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Based on content analyses of major US media, immediately following the George Floyd killing in May 2020, some mayors and local, state, and national officials offered favorable representations of protests against police violence. As the protest movement grew to historic proportions with 26 million joining actions in large cities and small towns, dominant representations of racism by elected officials and leading media shifted—replacing both the voices and demands of protestors with representations by elected officials. Major media quoted Black mayors and Congressional representatives who emphasized concerns about looting and the disruption of public safety. Media coverage privileged elected officials who criticized movement demands for defunding police and deplored isolated instances of property damaged by protestors. Subsequently, public opinion polls saw an increase in concern for law and order tropes and a decrease in support for protests against police violence. Black Lives Matter and local organizations had no coordinated response and no effective means of communication to counter dominant representations voiced by politicians and globally disseminated by major media. Politician and media-instigated public opinion shifts indicate that social movements need their own means of communication and collective decision-making--both of which were largely missing from Black Lives Matter leaders, leading to disaffection and a political split by more than 20 local affiliates. By itself, social media by myriad individuals and groups had limited purchase as a means for social movement communication and organization. Lacking a collaborative, coordinated strategy, organization, and independent media, the loose network of Black Lives Matter groups was unable to offer more accurate, democratic, and favorable representations of protests and their demands for more justice and equality. The fight for equality was diverted by the fight for representation.

Keywords: black lives matter, public opinion, racism, representations, social movements

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Authors: Ibrahim Yerima Gwalem, Jamila Ahmed Buhari

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In recent years, there has been an alarming rate of increase in the costs of building materials in Nigeria, and this ugly phenomenon threatens the contributions of the construction industry in national development. The purpose of this study was to assess the effects of the rising cost of building materials in Adamawa State Nigeria. Four research questions in line with the purpose of the study were raised to guide the study. Two null hypotheses were formulated and tested at 0.05 level of significance. The study adopted a survey research design. The population of the study comprises registered contractors, registered builders, selected merchants, and consultants in Adamawa state. Data were collected using researcher designed instrument tagged effects of the rising cost of building materials questionnaire (ERCBMQ). The instrument was subjected to face and content validation by two experts, one from Modibbo Adama University of Technology Yola and the other from Federal Polytechnic Mubi. The reliability of the instrument was determined by the Cronbach Alpha method and yielded a reliability index of 0.85 high enough to ascertain the reliability. Data collected from a field survey of 2019 was analyzed using mean and percentage. The means of the prices were used in the calculations of price indices and rates of inflation on building materials. Findings revealed that factors responsible for the rising cost of building materials are the exchange rate of the Nigeria Naira with a mean rating (MR) = 4.4; cost of fuel and power supply, MR = 4.3; and changes in government policies and legislation, MR = 4.2, while fluctuations in the construction cost with MR = 2.8; reduced volume of construction output, MR = 2.52; and risk of project abandonment, MRA = 2.51, were the three effects. The study concluded that adverse effects could result in a downward effect on the contributions of the construction industries on the gross domestic product (GDP) in the nation’s economy. Among the recommendations proffered include that the government should formulate a policy that will play down the agitations on the use of imported building materials by encouraging research in the production of local building materials.

Keywords: effects, rising, cost, building, materials

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Authors: Belinda Vega, Claudio Alvarez, Héctor Flores, Marcia Oliva, Katherine Alveal, Teresa Toro, María José Tapia, Fanny Guzmán

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With the increase in global temperatures and the decrease of oxygen (O2) concentration in the oceans, fish cultures are exposed to frequent fluctuations in dissolved O2 (DO) concentration that can cause chronic stress in the animals, altering the normal functioning of their immune system and making them vulnerable to infections, consequently increasing morbidity and mortality in the farms with economic losses. The mucosal organs (skin -and mucus-, gills, gut, and nasal mucosa) are the first line of defense of the fish against pathogens. Therefore, the objective of this study is to evaluate the effect of hypoxia on the antimicrobial activity of epidermal mucus from corvina drum (Cilus Gilberti), a native marine species with the potential for the diversification of aquaculture in Chile. To achieve this, the epidermal mucus of juveniles (~220g) kept under normoxia (7 mg/L DO) and hypoxia (2 mg/L DO) environmental conditions was collected after 6 weeks, as well as after 6 days of intraperitoneal inoculation with lipopolysaccharide from Vibrio anguillarum to induce an immune response in the fish. Total protein extracts of the mucus were used for bactericidal activity and lysozyme and peroxidase activity assays. Although the mucus from both experimental groups showed inhibitory effects on the bacterial growth of Vibrio anguillarum and Vibrio ordalli, this effect was more long-lasting in the normoxia group. We also observed a notable reduction in the presence of lysozyme in the mucus from fish exposed to hypoxia, with no differences in peroxidase content. Future proteomic studies of corvina mucus associated with the environmental conditions studied in this work will allow the isolation and identification of peptides with antimicrobial activity, those responsible for the results obtained. This will help establish strategies aimed at minimizing the impacts of hypoxia on the defense responses of corvina drum against potential pathogens. Funding: FONDECYT 3200440 and FONDECYT 1210056

Keywords: Cilus gilberti, mucus, antimicrobial activity, HYPOXIA

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Authors: Arfan Ali Nagra, Tariq Shahzad, Meshal Alharbi, Khalid Masood Khan, Muhammad Mugees Asif, Taher M. Ghazal, Khmaies Ouahada

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Gene selection is an essential step for the classification of microarray cancer data. Gene expression cancer data (DNA microarray) facilitates computing the robust and concurrent expression of various genes. Particle swarm optimization (PSO) requires simple operators and less number of parameters for tuning the model in gene selection. The selection of a prognostic gene with small redundancy is a great challenge for the researcher as there are a few complications in PSO based selection method. In this research, a new variant of PSO (Self-inertia weight adaptive PSO) has been proposed. In the proposed algorithm, SIW-APSO-ELM is explored to achieve gene selection prediction accuracies. This new algorithm balances the exploration capabilities of the improved inertia weight adaptive particle swarm optimization and the exploitation. The self-inertia weight adaptive particle swarm optimization (SIW-APSO) is used to search the solution. The SIW-APSO is updated with an evolutionary process in such a way that each particle iteratively improves its velocities and positions. The extreme learning machine (ELM) has been designed for the selection procedure. The proposed method has been to identify a number of genes in the cancer dataset. The classification algorithm contains ELM, K- centroid nearest neighbor (KCNN), and support vector machine (SVM) to attain high forecast accuracy as compared to the start-of-the-art methods on microarray cancer datasets that show the effectiveness of the proposed method.

Keywords: microarray cancer, improved PSO, ELM, SVM, evolutionary algorithms

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Authors: Aoife Prendergast

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The synergy between theory and practice can be considered elusive, the touchstone for the development of successful undergraduate programmes particularly in allied health professions such as social care. A 'pracademic' is a person who spans both the somewhat ethereal world of academia as a scholar and the pragmatic world of practice. This paper examines the concept of 'pracademia' in relation to the role of the social care practitioner and continuing professional development. It also assists in the understanding of the synergy between social care professionals and higher education. A consideration of the identity and position in terms of approach to regulation is explored as well as an acknowledgement of the strengths and opportunities for sharing power in hierarchical positions. The world of practice serves as the centre point of the academic compass for most professional programs. Just as schools of engineering and law are disciplined by the marketplace, which seeks well-trained students, so our social care programmes must perennially find ways to address the fast changing needs of practitioners, whether they be government, not-for-profit organizations, consulting firms or contractors. We may not expect such traditional academic disciplines as history, sociology, or political science to cater to the needs of external audiences or practitioners— indeed, these disciplines' insulation from public concerns and issues is considered a strength by some. This paper aims to explore the integration of academic teaching and research with the communities of practice in social care. This appears to be a fundamental aspiration of the social care profession. While building and integrating an important body of academic theory and concepts from a variety of disciplines, social care as a field has embraced a professional orientation by seeking to be relevant to practitioners at various levels. While teaching theory, social care programmes, and faculty are often acutely aware that their academic content and credibility, in part, rest on a deep connection with practitioners. While theory can be self-contained, the impact of our research and teaching arguably finds its most compelling and highest audience when it addresses the agenda items and concerns of practitioners.

Keywords: social care, pracademia, supervision, practice education

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Authors: Kasidis Chomrat, Nopasit Chakpitak, Anukul Tamprasirt, Annop Thananchana

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Internet of Things devices or IoT and Edge Computing has become one of the biggest things happening in innovations and one of the most discussed of the potential to improve and disrupt traditional business and industry alike. With rises of new hang cliff challenges like COVID-19 pandemic that posed a danger to workforce and business process of the system. Along with drastically changing landscape in business that left ruined aftermath of global COVID-19 pandemic, looming with the threat of global energy crisis, global warming, more heating global politic that posed a threat to become new Cold War. How emerging technology like edge computing and usage of specialized design visual processing units will be great opportunities for business. The literature reviewed on how the internet of things and disruptive wave will affect business, which explains is how all these new events is an effect on the current business and how would the business need to be adapting to change in the market and world, and example test benchmarking for consumer marketed of newer devices like the internet of things devices equipped with new edge computing devices will be increase efficiency and reducing posing a risk from a current and looming crisis. Throughout the whole paper, we will explain the technologies that lead the present technologies and the current situation why these technologies will be innovations that change the traditional practice through brief introductions to the technologies such as cloud computing, edge computing, Internet of Things and how it will be leading into future.

Keywords: internet of things, edge computing, machine learning, pattern recognition, image classification

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Authors: Majid Amidpour, Parisa Karimi, Marzieh Joda

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For the last few years, release of burned undesirable by-products has become a challenging issue in oil industries. Flaring, as one of the main sources of air contamination, involves detrimental and long-lasting effects on human health and is considered a substantial reason for energy losses worldwide. This research involves studying the implications of two main flare gas recovery methods at three oil refineries, all in Iran as the case I, case II, and case III in which the production capacities are increasing respectively. In the proposed methods, flare gases are converted into more valuable products, before combustion by the flare networks. The first approach involves collecting, compressing and converting the flare gas to smokeless fuel which can be used in the fuel gas system of the refineries. The other scenario includes utilizing the flare gas as a feed into liquefied petroleum gas (LPG) production unit already established in the refineries. The processes of these scenarios are simulated, and the capital investment is calculated for each procedure. The cumulative profits of the scenarios are evaluated using Net Present Value method. Furthermore, the sensitivity analysis based on total propane and butane mole fraction is carried out to make a rational comparison for LPG production approach, and the results are illustrated for different mole fractions of propane and butane. As the mole fraction of propane and butane contained in LPG differs in summer and winter seasons, the results corresponding to LPG scenario are demonstrated for each season. The results of the simulations show that cumulative profit in fuel gas production scenario and LPG production rate increase with the capacity of the refineries. Moreover, the investment return time in LPG production method experiences a decline, followed by a rising trend with an increase in C₃ and C₄ content. The minimum value of time return occurs at propane and butane sum concentration values of 0.7, 0.6, and 0.7 in case I, II, and III, respectively. Based on comparison of the time of investment return and cumulative profit, fuel gas production is the superior scenario for three case studies.

Keywords: flare gas reduction, liquefied petroleum gas, fuel gas, net present value method, sensitivity analysis

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Authors: Gina Cecilia Pistol, Loredana Calin, Mariana Stancu, Veronica Chedea, Ionelia Taranu

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Inflammatory-associated diseases have an increased trend in the past decades. The pharmacological strategies aimed to treat these inflammatory diseases are very expensive and with non-beneficial results. The current trend is to find alternative strategies to counteract or to control inflammatory component of diseases. The grape by-products either seeds or pomace are rich in bioactive compounds (e.g. polyphenols) which may be beneficial in prevention of inflammation associated with cancer progression and other pathologies with inflammatory component. The in vivo models are very useful for studying the immune and inflammatory status. The domestic pig (Sus scrofa domesticus) is related to human from anatomic and physiologic point of view, representing a feasible model for studying the human inflammatory pathologies. Starting from these data, we evaluated the effect of a diet containing 5% grape seed cakes (GS) on piglets blood biochemical parameters and immune pro- and anti-inflammatory biomarkers (IL-1 beta, IL-8, TNF-alpha, IL-6, IFN-gamma, IL-10, IL-4) in spleen and lymph nodes. 12 weaned piglets were fed for 30 days with a control diet or an experimental diet containing 5% GS. At the end of trial, plasma and tissue samples (spleen and lymph nodes) were collected and the biochemical and inflammatory markers were analysed by using biochemistry analyser and ELISA techniques. Our results showed that diet included 5% GS did not influence the health status determined by plasma biochemical parameters. Only a tendency for a slight increase of the biochemical parameters associated with energetic profile (glucose, cholesterol, triglycerides) was observed. Also, GS diet had no effect on pro- and anti-inflammatory cytokines content in spleen and lymph nodes tissue. Further experiments are needed in order to investigate other rate of dietary inclusion which could provide more evidence about the effect of grape bioactive compounds on pigs used as animal model.

Keywords: animal model, inflammation, grape seed by-product, immune organs

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Authors: Medhanie Gebremedhin Gebru, Alex Schechter

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Dimethyl ether (DME) possesses several advantages over other small organic molecules such as methanol, ethanol, and ammonia in terms of providing higher energy density, being less toxic, and having lower Nafion membrane crossover. However, the absence of an active and stable catalyst has been the bottleneck that hindered the commercialization of direct DME fuel cells. A Vulcan XC72 carbon-supported ternary metal catalyst, Pt₃Pd₃Sn₂/C is reported to have yielded the highest specific power density (90 mW mg-¹PGM) as compared to other catalysts tested fordirect DME fuel cell (DDMEFC). However, the micropores and sulfur groups present in Vulcan XC72 hinder the fuel utilization by causing Pt agglomeration and sulfur poisoning. Vulcan XC72 having a high carbon sp³ hybridization content, is also prone to corrosion. Therefore, carbon supports such as multi-walled carbon nanotube (MWCNT), black pearl 2000 (BP2000), and their cold N2 plasma-treated counterpartswere tested to further enhance the activity of the catalyst, and the outputs with these carbons were compared with the originally used support. Detailed characterization of the pristine and carbon supports was conducted. Electrochemical measurements in three-electrode cells and laboratory prototype fuel cells were conducted.Pt₃Pd₃Sn₂/BP2000 exhibited excellent performance in terms of electrochemical active surface area (ECSA), peak current density (jp), and DME oxidation charge (Qoxi). The effect of the plasma activation on the activity improvement was observed only in the case of MWCNT while having little or no effect on the other carbons. A Pt₃Pd₃Sn₂ supported on the optimized mixture of carbons containing 75% plasma-activated MWCNT and 25% BP2000 (Pt₃Pd₃Sn₂/75M25B) provided the highest reported power density of 117 mW mg-1PGM using an anode loading of1.55 mgPGMcm⁻².

Keywords: DME, DDMEFC, ternary metal catalyst, carbon support, plasma activation

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Authors: Iwan Cony Setiadi, Aulia M. T. Nasution

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The multispectral imaging (MSI) technique has been used for skin analysis, especially for distant mapping of in-vivo skin chromophores by analyzing spectral data at each reflected image pixel. For ergonomic purpose, our multispectral imaging system is decomposed in two parts: a light source compartment based on LED with 11 different wavelenghts and a monochromatic 8-Bit CCD camera with C-Mount Objective Lens. The software based on GUI MATLAB to control the system was also developed. Our system provides 11 monoband images and is coupled with a software reconstructing hyperspectral cubes from these multispectral images. In this paper, we proposed a new method to build a hyperspectral reflectance cube based on artificial neural network algorithm. After preliminary corrections, a neural network is trained using the 32 natural color from X-Rite Color Checker Passport. The learning procedure involves acquisition, by a spectrophotometer. This neural network is then used to retrieve a megapixel multispectral cube between 380 and 880 nm with a 5 nm resolution from a low-spectral-resolution multispectral acquisition. As hyperspectral cubes contain spectra for each pixel; comparison should be done between the theoretical values from the spectrophotometer and the reconstructed spectrum. To evaluate the performance of reconstruction, we used the Goodness of Fit Coefficient (GFC) and Root Mean Squared Error (RMSE). To validate reconstruction, the set of 8 colour patches reconstructed by our MSI system and the one recorded by the spectrophotometer were compared. The average GFC was 0.9990 (standard deviation = 0.0010) and the average RMSE is 0.2167 (standard deviation = 0.064).

Keywords: multispectral imaging, reflectance cube, spectral reconstruction, artificial neural network

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Authors: Elnaz Kanani-Kuchesfehani, Andrea Schiffauerova

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Due to the novelty of the nanotechnology science, its highly knowledge intensive content, and its invaluable application in almost all technological fields, the close interaction between university and industry is essential. A possible gap between academic strengths to generate good nanotechnology ideas and industrial capacity to receive them can thus have far-reaching consequences. In order to be able to enhance the collaboration between the two parties, a better understanding of knowledge transfer within the university-industry relationship is needed. The objective of this research is to investigate the research collaboration between academia and industry in Canadian nanotechnology and to propose the best cooperative strategy to maximize the quality of the produced knowledge. First, a network of all Canadian academic and industrial nanotechnology inventors is constructed using the patent data from the USPTO (United States Patent and Trademark Office), and it is analyzed with social network analysis software. The actual level of university-industry collaboration in Canadian nanotechnology is determined and the significance of each group of actors in the network (academic vs. industrial inventors) is assessed. Second, a novel methodology is proposed, in which the network of nanotechnology inventors is assessed from a game theoretic perspective. It involves studying a cooperative game with n players each having at most n-1 decisions to choose from. The equilibrium leads to a strategy for all the players to choose their co-worker in the next period in order to maximize the correlated payoff of the game. The payoffs of the game represent the quality of the produced knowledge based on the citations of the patents. The best suggestion for the next collaborative relationship is provided for each actor from a game theoretic point of view in order to maximize the quality of the produced knowledge. One of the major contributions of this work is the novel approach which combines game theory and social network analysis for the case of large networks. This approach can serve as a powerful tool in the analysis of the strategic interactions of the network actors within the innovation systems and other large scale networks.

Keywords: cooperative strategy, game theory, industry-university collaboration, knowledge production, social network analysis

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Authors: Simona Lucakova, Irena Branyikova

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Eutrophication, a condition when water becomes over-enriched with nutrients (P, N), can lead to undesirable excessive growth of phytoplankton, so-called algal bloom. This process results in the accumulation of toxin-producing cyanobacteria and oxygen depletion, both possibly leading to the collapse of the whole ecosystem. In real conditions, the limiting nutrient, which determines the possible growth of harmful algal bloom, is usually phosphorus. Algicides or flocculants have been applied in the eutrophicated waterbody in order to reduce the phytoplankton growth, which leads to the introduction of toxic chemicals into the water. In our laboratory, the idea of the prevention of harmful phytoplankton growth by the intentional cultivation of non-toxic cyanobacteria Tolypothrix tenuis in semi-open floating photobioreactors directly on the surface of phosphorus-rich waterbody is examined. During the process of cultivation, redundant phosphorus is incorporated into cyanobacterial biomass, which can be subsequently used for the production of biofuels, cosmetics, pharmaceuticals, or biostimulants for agricultural use. To determine the ability of phosphorus incorporation, batch-cultivation of Tolypothrix biomass in media simulating eutrophic water (10% BG medium) and in effluent from municipal wastewater treatment plant, both with the initial phosphorus concentration in the range 0.5-1.0 mgP/L was performed in laboratory-scale models of floating photobioreactors. After few hours of cultivation, the phosphorus content was decreased below the target limit of 0.035 mgP/L, which was given as a borderline for the algal bloom formation. Under laboratory conditions, the effect of several parameters on the rate of phosphorus decrease was tested (illumination, temperature, stirring speed/aeration gas flow, biomass to medium ratio). Based on the obtained results, a bench-scale floating photobioreactor was designed and will be tested for Tolypothrix growth in real conditions. It was proved that intentional cultivation of cyanobacteria Tolypothrix could be a suitable approach for extracting redundant phosphorus from eutrophic waters as prevention of algal bloom formation.

Keywords: cyanobacteria, eutrophication, floating photobioreactor, Tolypothrix

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Authors: Kehinde, Taye Adetutu

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The fact that Nigeria as a nation is faced by myriads of problems associated with religious crises and political insecurity is no news, the spoken statement and actions of most political giant were the major cause of this unrest. The 'unlearnt' youth within the regions has encompassed the situation. This scenario is further compounded by multilingual nature of the country as it is estimated that there exists amount 400 indigenous languages in Nigeria. It is an indisputable fact that english language which has assumed the status of an official language in Nigeria, given its status has a language of power and captivity by a few with no privilege to attend school. However, educating people in their indigenous language; crises can be averted through the proper orientation and mass literacy campaign, especially for the timid illiterate one, so as to live in unity, peace, tranquillity, and harmony as indivisible nation. In investigating the problem in this study with an emphasis on three major Nigerian language (Yoruba, Igbo and Hausa), participants observations and survey questionnaire were administered to about one hundred and twenty (120) respondents who were randomly selected throughout the three major ethnic groups in Nigeria. Findings from this study reveals that teaching and learning of cognitive words and information are more effective in ones mother tongue and helps in stimulating new ideas and changes. This paper was able to explore and critically examine the current state of affairs in Nigeria and proffer possible solutions to the prevailing situations by identifying how indigenous languages and linguistics can be used to ameliorate the present political and religious crisis for Nigeria, thus providing a proper recommendation to achieve meaningful stability and coexistence within a nation.

Keywords: multilingualism, political crisis, religious, Nigeria

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: conditional generative adversarial net, market and credit risk management, neural network, time series

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Authors: Pedro Llanos, Diego García

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This paper is addressed to expanding our understanding of the effects of hypoxia training on our bodies to better model its dynamics and leverage some of its implications and effects on human health. Hypoxia training is a recommended practice for military and civilian pilots that allow them to recognize their early hypoxia signs and symptoms, and Scientist Astronaut Candidates (SACs) who underwent hypobaric hypoxia (HH) exposure as part of a training activity for prospective suborbital flight applications. This observational-analytical study describes physiologic responses and symptoms experienced by a SAC group before, during and after HH exposure and proposes a model for assessing predicted versus observed physiological responses. A group of individuals with diverse Science Technology Engineering Mathematics (STEM) backgrounds conducted a hypobaric training session to an altitude up to 22,000 ft (FL220) or 6,705 meters, where heart rate (HR), breathing rate (BR) and core temperature (Tc) were monitored with the use of a chest strap sensor pre and post HH exposure. A pulse oximeter registered levels of saturation of oxygen (SpO₂), number and duration of desaturations during the HH chamber flight. Hypoxia symptoms as described by the SACs during the HH training session were also registered. This data allowed to generate a preliminary predictive model of the oxygen desaturation and O₂ pressure curve for each subject, which consists of a sixth-order polynomial fit during exposure, and a fifth or fourth-order polynomial fit during recovery. Data analysis showed that HR and BR showed no significant differences between pre and post HH exposure in most of the SACs, while Tc measures showed slight but consistent decrement changes. All subjects registered SpO₂ greater than 94% for the majority of their individual HH exposures, but all of them presented at least one clinically significant desaturation (SpO₂ < 85% for more than 5 seconds) and half of the individuals showed SpO₂ below 87% for at least 30% of their HH exposure time. Finally, real time collection of HH symptoms presented temperature somatosensory perceptions (SP) for 65% of individuals, and task-focus issues for 52.5% of individuals as the most common HH indications. 95% of the subjects experienced HH onset symptoms below FL180; all participants achieved full recovery of HH symptoms within 1 minute of donning their O₂ mask. The current HH study performed on this group of individuals suggests a rapid and fully reversible physiologic response after HH exposure as expected and obtained in previous studies. Our data showed consistent results between predicted versus observed SpO₂ curves during HH suggesting a mathematical function that may be used to model HH performance deficiencies. During the HH study, real-time HH symptoms were registered providing evidenced SP and task focusing as the earliest and most common indicators. Finally, an assessment of HH signs of symptoms in a group of heterogeneous, non-pilot individuals showed similar results to previous studies in homogeneous populations of pilots.

Keywords: slow onset hypoxia, hypobaric chamber training, altitude sickness, symptoms and altitude, pressure cabin

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Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

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Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

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Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

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Authors: Andres Gonzalez, Adam Boies, Jacob Swanson, David Kittelson

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The concern of the indoor air quality (IAQ) has been increasing due to its risk to human health. The smoking, sweeping, and stove and stovetop use are the activities that have a major contribution to the indoor air pollution. Outdoor air pollution also affects IAQ. The most important factors over IAQ from cooking activities are the materials, fuels, foods, and ventilation. The low-cost, mobile air quality monitoring (LCMAQM) sensors, is reachable technology to assess the IAQ. This is because of the lower cost of LCMAQM compared to conventional instruments. The IAQ was assessed, using LCMAQM, during cooking activities in a University of Minnesota graduate-housing evaluating different ventilation systems. The gases measured are carbon monoxide (CO) and carbon dioxide (CO₂). The particles measured are particle matter (PM) _2.5 micrometer (µm) and lung deposited surface area (LDSA). The measurements are being conducted during April 2019 in Como Student Community Cooperative (CSCC) that is a graduate housing at the University of Minnesota. The measurements are conducted using an electric stove for cooking. The amount and type of food and oil using for cooking are the same for each measurement. There are six measurements: two experiments measure air quality without any ventilation, two using an extractor as mechanical ventilation, and two using the extractor and windows open as mechanical and natural ventilation. 3The results of experiments show that natural ventilation is most efficient system to control particles and CO₂. The natural ventilation reduces the concentration in 79% for LDSA and 55% for PM_2.5, compared to the no ventilation. In the same way, CO₂ reduces its concentration in 35%. A well-mixed vessel model was implemented to assess particle the formation and decay rates. Removal rates by the extractor were significantly higher for LDSA, which is dominated by smaller particles, than for PM_2.5, but in both cases much lower compared to the natural ventilation. There was significant day to day variation in particle concentrations under nominally identical conditions. This may be related to the fat content of the food. Further research is needed to assess the impact of the fat in food on particle generations.

Keywords: cooking, indoor air quality, low-cost sensor, ventilation

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Authors: Kanokwan Sansuwan, Orapint Jintasataporn, Srinoy Chumkam

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Asian seabass is one of the economically important fish of Thailand and other countries in the Southeast Asia. Zinc is an essential trace metal to fish and vital to various biological processes and function. It is required for normal growth and indispensable in the diet. Therefore, the artificial diets offered to intensively cultivated fish must possess the zinc content required by the animal metabolism for health maintenance and high weight gain rates. However, essential elements must also be in an available form to be utilized by the organism. Thus, this study was designed to evaluate the application of different zinc forms, including organic Zinc (zinc amino acid complex) and inorganic Zinc (zinc sulfate), as feed additives in diets for Asian seabass. Three groups with five replicates of fish (mean weight 22.54 ± 0.80 g) were given a basal diet either unsupplemented (control) or supplemented with 50 mg Zn kg−¹ sulfate (ZnSO₄) or Zinc Amino Acid Complex (ZnAA) respectively. Feeding regimen was initially set at 3% of body weight per day, and then the feed amount was adjusted weekly according to the actual feeding performance. The experiment was conducted for 10 weeks. Fish supplemented with ZnAA had the highest values in all studied growth indicators (weight gain, average daily growth and specific growth rate), followed by fish fed the diets with the ZnSO₄, and lowest in fish fed the diets with the control. Lysozyme and superoxide dismutase (SOD) activity of fish supplemented with ZnAA were significantly higher compared with all other groups (P < 0.05). Fish supplemented with ZnSO₄ exhibited significant increase in digestive enzyme activities (protease, pepsin and trypsin) compared with ZnAA and the control (P < 0.05). However, no significant differences were observed for RNA and protein in muscle (P > 0.05). The results of the present work suggest that ZnAA are a better source of trace elements for Asian seabass, based on growth performance and immunity indices examined in this study.

Keywords: Asian seabass, growth performance, zinc amino acid complex (ZnAA), zinc sulfate (ZnSO₄)

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Authors: Julius K. Gane, Mohamad N. Nahil, Paul T. Williams

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In today’s world of rapid population growth and a changing climate, one way to mitigate various negative effects is via renewable energy solutions. Energy and power as basic requirements in almost all human endeavours are also the banes of the changing climate and the impacts thereof. Thus it is crucial to develop innovative and environmentally friendly energy options to ameliorate various negative repercussions. Upgrading of fast pyrolysis bio-oil via hydro-treatment offers such opportunities, as quality renewable liquid transportation fuels can be produced. The process, however, is typically accompanied by bio-char formation as a by-product. The goal of this work was to study the yield and some properties of bio-chars formed from a hydrotreatment process, with an overall aim to promote the valuable utilization of wastes or by-products from renewable energy technologies. It is assumed that bio-chars that have comparable energy contents with coals will be more desirable as solid energy materials due to renewability and environmental friendliness. Therefore, the analytical work in this study focused mainly on determining the higher heating value (HHV) of the chars. The method involved the reaction of bio-oil in an autoclave supplied by the Parr Instrument Company, IL, USA. Two main parameters (different temperatures and resident times) were investigated. The chars were characterized using a Thermo EA2000 CHNS analyser, then oxygen contents and HHVs computed based on the literature. From the results, these bio-chars can readily serve as feedstocks for the production of renewable solid fuels. Their HHVs ranged between 29.26-39.18 MJ/kg, affected by different temperatures and retention times. There was an inverse relationship between the oxygen content and the HHVs of the chars. It can, therefore, be concluded that it is possible to optimize the process efficiency of the hydrotreatment process used through the production of renewable energy materials from the 'waste’ char by-products. Future work should consider developing a suitable balance between the primary objective of bio-oil upgrading processes (which is to improve the quality of the liquid fuels) and the conversion of its solid wastes into value-added products such as smokeless briquettes.

Keywords: bio-char, renewable solid biofuels, valorisation, waste-to-energy

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Authors: Emilie Zimet

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During networking and NCCD moderation meetings, best practices for identifying students who require Literacy Intervention are often discussed. Once these students are identified, consideration is given to the most effective process for prioritising those who have the greatest need for Literacy Support and the allocation of resources, tracking of intervention effectiveness and communicating with teachers/external providers/parents. Through a workshop, the group will investigate best practices to identify students who require literacy support and strategies to communicate and track their progress. In groups, participants will examine what they do in their settings and then compare with other models, including the researcher’s model, to decide the most effective path to identification and communication. Participants will complete a worksheet at the beginning of the session to deeply consider their current approaches. The participants will be asked to critically analyse their own identification processes for Literacy Intervention, ensuring students are not overlooked if they fall into the borderline category. A cut-off for students to access intervention will be considered so as not to place strain on already stretched resources along with the most effective allocation of resources. Furthermore, communicating learning needs and differentiation strategies to staff is paramount to the success of an intervention, and participants will look at the frequency of communication to share such strategies and updates. At the end of the session, the group will look at creating or evolving models that allow for best practices for the identification and communication of Literacy Interventions. The proposed outcome for this research is to develop a model of identification of students requiring Literacy Intervention that incorporates the allocation of resources and communication to key stakeholders. This will be done by pooling information and discussing a variety of models used in the participant's school settings.

Keywords: identification, student selection, communication, special education, school policy, planning for intervention

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Authors: Daniel Osieko Okach, Joseph Otieno Ondier, Gerhard Rambold, John Tenhunen, Bernd Huwe, Dennis Otieno

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Increased human activities such as grazing, logging, and agriculture alongside unpredictable rainfall patterns have been detrimental to the ecosystem service delivery, therefore compromising its productivity potential. This study aimed at simulating the impact of drought (50%) and enhanced rainfall (150%) on the future herbaceous CO2 uptake, biomass production and soil C:N dynamics in a humid savanna ecosystem influenced by livestock grazing. Rainfall pattern was predicted using manipulation experiments set up to reduce (50%) and increase (150%) ambient (100%) rainfall amounts in grazed and non-grazed plots. The impact of manipulated rainfall regime on herbaceous CO2 fluxes, biomass production and soil C:N dynamics was measured against volumetric soil water content (VWC) logged every 30 minutes using the 5TE (Decagon Devices Inc., Washington, USA) soil moisture sensors installed (at 20 cm soil depth) in every plots. Herbaceous biomass was estimated using destructive method augmented by standardized photographic imaging. CO2 fluxes were measured using the ecosystem chamber method and the gas analysed using LI-820 gas analyzer (USA). C:N ratio was calculated from the soil carbon and Nitrogen contents (analyzed using EA2400CHNS/O and EA2410 N elemental analyzers respectively) of different plots under study. The patterning of VWC was directly influenced by the rainfall amount with lower VWC observed in the grazed compared to the non-grazed plots. Rainfall variability, grazing and their interaction significantly affected changes in VWC (p < 0.05) and subsequently total biomass and CO2 fluxes. VWC had a strong influence on CO2 fluxes under 50% rainfall reduction in the grazed (r2 = 0.91; p < 0.05) and ambient rainfall in the ungrazed (r2 = 0.77; p < 0.05). The dependence of biomass on VWC across plots was enhanced under grazed (r2 = 0.78 - 0.87; p < 0.05) condition as compared to ungrazed (r2 = 0.44 - 0.85; p < 0.05). The C:N ratio was however not correlated to VWC across plots. This study provides insight on how the predicted trends in humid savanna will respond to changes influenced by rainfall variability and livestock grazing and consequently the sustainable management of such ecosystems.

Keywords: CO2 fluxes, rainfall manipulation, soil properties, sustainability

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Authors: Shadia Al-Bahlani, Ruqaya Al-Rashdi, Shadia Al-Sinawi, Maya Al-Bahri

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Background: Breast cancer is the most common cancer in women worldwide. Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer, which is defined by the absence of Estrogen (ER), Progesterone (PR) and Human epidermal growth factor (Her-2) receptors. The calpain system plays an important role in many cellular processes including apoptosis, necrosis, cell signaling and proliferation. The role of clapins in pathogenesis and tumor progression has been studied in certain cancer types; however, its definite role is not yet established in breast cancer especially in the TNBC subtype. Objectives: This study aims to measure calpain-1 expression and correlate this measurement with the proliferating/apoptotic index as well with the prognostic factors in TNBC patients’ tissue. Materials and Methods: Thirty nine paraffin blocks from patients diagnosed with TNBC were used to measure the expression of calpain-1 and Ki-67 (proliferating marker) proteins using immunohistochemistry. Apoptosis was assessed morphological and biochemically using conventional Haematoxylin and Eosin (H&E) staining method and terminal deoxynucleotidyl transferase-mediate dUTP nick and labeling (TUNEL) assay respectively. Data was statistically analyzed using Pearson X2 test of association. Results: Calpain-1 content was visualized in the nucleus of the TNBC cells and its expression varied from low to high among the patients tissue. Calpain expression showed no significant correlation with the proliferating/apoptotic index as well with the clinicopathological variables. Apoptotic counts quantified by H&E staining showed significant association with the apoptotic TUNEL assay, validating both approaches. Conclusion: Although calpain-1 expression showed no significant association with the clinical outcome, its variable level of expression might indicate a hidden role in breast cancer tissue. Larger number of samples and different mode of assessments are needed to fully investigate such role. Exploring the involvement of calpain-1 in cancer progression might help in considering it as a biomarker of breast cancer.

Keywords: breast cancer, calpain, apoptosis, prognosis

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Authors: Abel Olusegun Egunjobi, Olusegun Oyeleye Adesanya

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Teaching effectiveness of lecturers in a tertiary institution in Nigeria is one of the determinants of the lecturer’s productivity. In this study, therefore, lecturers’ teaching effectiveness was examined vis-à-vis their multimedia technologies utilisation in Colleges of Education (CoE) in South-West, Nigeria. This is for the purpose of ascertaining the relationship and contribution of multimedia technologies utilisation to lecturers’ teaching effectiveness in Nigerian colleges of education. The descriptive survey research design was adopted in the study, while a multi-stage sampling procedure was used in the study. A stratified sampling technique was used to select colleges of education, and a simple random sampling method was employed to select lecturers from the selected colleges of education. A total of 862 lecturers (627 males and 235 females) were selected from the colleges of education used for the study. The instrument used was lecturers’ questionnaire on multimedia technologies utilisation and teaching effectiveness with a reliability coefficient of 0.85 at 0.05 level of significance. The data collected were analysed using descriptive statistics, multiple regression, and t-test. The findings showed that the level of multimedia technologies utilisation in colleges of education was low, whereas lecturers’ teaching effectiveness was high. Findings also revealed that the lecturers used multimedia technologies purposely for personal and professional developments, so also for up to date news on economic and political matters. Also, findings indicated that laptop, Ipad, CD-ROMs, and computer instructional software were the multimedia technologies frequently utilised by the lecturers. There was also a significant difference in the teaching effectiveness between lecturers in the Federal and State COE. The government should, therefore, make adequate provision for multimedia technologies in the COE in Nigeria for lecturers’ utilisation in their instructions so as to boost their students’ learning outcomes.

Keywords: colleges of education, lecturers’ teaching effectiveness, multimedia technologies utilisation, Southwest Nigeria

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